scholarly journals Canal blocking optimization in restoration of drained peatlands

2020 ◽  
Vol 17 (19) ◽  
pp. 4769-4784
Author(s):  
Iñaki Urzainki ◽  
Ari Laurén ◽  
Marjo Palviainen ◽  
Kersti Haahti ◽  
Arif Budiman ◽  
...  
Keyword(s):  
Water Table ◽  
Hydraulic Properties ◽  
Hydrological Model ◽  
Initial State ◽  
Peatland Restoration ◽  
Canal Network ◽  
Carbon Dioxide Co2 ◽  
Water Saturated ◽  
Water Table Rise ◽  
Exact Positions

Abstract. Drained peatlands are one of the main sources of carbon dioxide (CO2) emissions globally. Emission reduction and, more generally, ecosystem restoration can be enhanced by raising the water table using canal or drain blocks. When restoring large areas, the number of blocks becomes limited by the available resources, which raises the following question: in which exact positions should a given number of blocks be placed in order to maximize the water table rise throughout the area? There is neither a simple nor an analytic answer. The water table response is a complex phenomenon that depends on several factors, such as the topology of the canal network, site topography, peat hydraulic properties, vegetation characteristics and meteorological conditions. We developed a new method to position the canal blocks based on the combination of a hydrological model and heuristic optimization algorithms. We simulated 3 d dry downs from a water saturated initial state for different block positions using the Boussinesq equation, and the block configurations maximizing water table rise were searched for by means of genetic algorithm and simulated annealing. We applied this approach to a large drained peatland area (931 km2) in Sumatra, Indonesia. Our solution consistently outperformed traditional block locating methods, indicating that drained peatland restoration can be made more effective at the same cost by selecting the positions of the blocks using the presented scheme.

scholarly journals Canal blocking optimization in restoration of drained peatlands

2020 ◽  
Author(s):  
Iñaki Urzainki ◽  
Ari Laurén ◽  
Marjo Palviainen ◽  
Kersti Haahti ◽  
Arif Budiman ◽  
...  
Keyword(s):  
Water Table ◽  
Hydraulic Properties ◽  
Hydrological Model ◽  
Ecosystem Restoration ◽  
Meteorological Conditions ◽  
Peatland Restoration ◽  
Canal Network ◽  
Vegetation Characteristics ◽  
Carbon Dioxide Co2 ◽  
Exact Positions

Abstract. Drained peatlands are one of the main sources of carbon dioxide (CO2) emissions globally. Emission reduction and, more generally, ecosystem restoration can be achieved by raising the water table using canal or drain blocks. When restoring large areas, the number of blocks becomes limited by the available resources, which raises the following question: in which exact positions should a given number of blocks be placed in order to maximize the water table raise throughout the area? There is neither a simple nor an analytic answer. The water table response is a complex phenomenon that depends on several factors, such as the topology of the canal network, site topography, peat hydraulic properties, vegetation characteristics and meteorological conditions. We developed a new method to position the canal blocks based on the combination of a hydrological model and heuristic optimization algorithms. We applied this approach to a large drained peatland area (931 km2) in Sumatra, Indonesia. Our solution consistently improved the performance of traditional block locating methods, indicating that drained peatland restoration can be made more effective at the same cost by selecting the positions of the blocks using the presented scheme.

Canal block location optimization for drained peatland restoration

2020 ◽  
Author(s):  
Iñaki Urzainqui ◽  
Ari Laurén ◽  
Marjo Palviainen ◽  
Hannu Hökkä
Keyword(s):  
Water Table ◽  
Hydraulic Properties ◽  
Hydrological Model ◽  
Ecosystem Restoration ◽  
Numerical Approach ◽  
Meteorological Conditions ◽  
Location Optimization ◽  
Peatland Restoration ◽  
Canal Network ◽  
Exact Positions

<p><span>Building canal or drain blocks is a powerful tool to raise the water table of a drained peatland and to enhance ecosystem restoration. When restoring large areas, the number of blocks becomes limited by the available resources, which raises the following question: in which exact positions should a given number of blocks be placed in order to maximize the water table raise? There is neither a simple nor an analytic answer. The water table response is a complex phenomenon that depends on several factors, such as the topology of the canal network, site topography, peat hydraulic properties, vegetation and meteorological conditions. We developed a new method to position the canal blocks which is based on the combination of a hydrological model and heuristic optimization algorithms. We applied this approach to a large drained peatland area (1100 km</span><sup><span>2</span></sup><span>) in Indonesia. Our solution consistently improved the performance of traditional block locating methods, indicating that drained peatland restoration can be made more effective at the same cost by selecting the positions of the blocks using a numerical approach.</span></p>

scholarly journals Comment on "Soil CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O fluxes from an afforested lowland raised peat bog in Scotland: implications for drainage and restoration" by Yamulki et al. (2013)

2013 ◽  
Vol 10 (11) ◽  
pp. 7623-7630 ◽  
Author(s):  
R. R. E. Artz ◽  
S. J. Chapman ◽  
M. Saunders ◽  
C. D. Evans ◽  
R. B. Matthews
Keyword(s):  
Carbon Dioxide ◽  
Nitrous Oxide ◽  
Ghg Emissions ◽  
Peat Bog ◽  
Raised Bog ◽  
Land Use Conversion ◽  
Peatland Restoration ◽  
Carbon Dioxide Equivalents ◽  
Carbon Dioxide Co2 ◽  
Chamber Measurements

Abstract. Yamulki and co-authors address in their recent publication the important issue of net emissions of greenhouse gases (GHGs) from peatlands where land use conversion has taken place. In their case, they studied conversion to forestry versus peatland restoration after a first rotation of plantation forestry. They monitored soil-derived fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) using opaque chamber measurements on planted and unplanted control treatments (with or without drainage), and an unplanted plot within a restored (felled) block on former lowland raised bog. They propose that their measurements of greenhouse gas (GHG) emissions at these sites suggest that the total net GHG emissions, in 100 yr carbon dioxide equivalents, of the restored peat bog would be higher than that of the peat bog with trees. We believe there are a number of issues with the measurement, calculation and comparison of these greenhouse budgets that may invalidate this conclusion.

scholarly journals Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: effect of preprocessing and postprocessing on skill and statistical consistency

2017 ◽  
Author(s):  
Diana Lucatero ◽  
Henrik Madsen ◽  
Jens C. Refsgaard ◽  
Jacob Kidmose ◽  
Karsten H. Jensen
Keyword(s):  
Hydrological Model ◽  
Predictive Distribution ◽  
Low Flow ◽  
Model Errors ◽  
Streamflow Prediction ◽  
Initial State ◽  
Lower Accuracy ◽  
Spatially Distributed ◽  
Streamflow Forecasts ◽  
Statistical Consistency

Abstract. In the present study we analyze the effect of bias adjustments in both meteorological and streamflow forecasts on skill and reliability of monthly average streamflow and low flow forecasts. Both raw and pre-processed meteorological seasonal forecast from the European Center for Medium-Range Weather Forecasts (ECMWF) are used as inputs to a spatially distributed, coupled surface – subsurface hydrological model based on the MIKE SHE code in order to generate streamflow predictions up to seven months in advance. In addition to this, we postprocess streamflow predictions using an empirical quantile mapping that adjusts the predictive distribution in order to match the observed one. Bias, skill and statistical consistency are the qualities evaluated throughout the forecast generating strategies and we analyze where the different strategies fall short to improve them. ECMWF System 4-based streamflow forecasts tend to show a lower accuracy level than those generated with an ensemble of historical observations, a method commonly known as Ensemble Streamflow Prediction (ESP). This is particularly true at longer lead times, for the dry season and for streamflow stations that exhibit low hydrological model errors. Biases in the mean are better removed by postprocessing that in turn is reflected in the higher level of statistical consistency. However, in general, the reduction of these biases is not enough to ensure a higher level of accuracy than the ESP forecasts. This is true for both monthly mean and minimum yearly streamflow forecasts. We highlight the importance of including a better estimation of the initial state of the catchment, which will increase the capability of the system to forecast streamflow at longer leads.

scholarly journals On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment

2019 ◽  
Author(s):  
Maxime Jay-Allemand ◽  
Pierre Javelle ◽  
Igor Gejadze ◽  
Patrick Arnaud ◽  
Pierre-Olivier Malaterre ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Weather Forecasting ◽  
Flash Flood ◽  
Estimation Method ◽  
Distributed Hydrological Model ◽  
Initial State ◽  
Ungauged Catchments ◽  
Temporal Dimension ◽  
Radar Rainfall ◽  
Additional Constraints

Abstract. Flash flood alerts in metropolitan France are provided by SCHAPI (Service Central Hydrométéorologique et d’Appui à la Prévision des Inondations) through the Vigicrues Flash service, which is designed to work in ungauged catchments. The AIGA method implemented in Vigicrues Flash is designed for flood forecasting on small- and medium-scale watersheds. It is based on a distributed hydrological model accounting for spatial variability of the rainfall and the catchment properties, based on the radar rainfall observation inputs. Calibration of distributed parameters describing these properties with high resolution is difficult, both technically (in terms of the estimation method), and because of the identifiability issues. Indeed, the number of parameters to be calibrated is much greater than the number of spatial locations where the discharge observations are usually available. However, the flood propagation is a dynamic process, so observations have also a temporal dimension. This must be larger enough to comprise a representative set of events. In order to fully benefit from using the AIGA method, we consider its hydrological model (GRD) in combination with the variational estimation (data assimilation) method. In this method, the optimal set of parameters is found by minimizing the objective function which includes the misfit between the observed and predicted values and some additional constraints. The minimization process requires the gradient of the cost function with respect to all control parameters, which is efficiently computed using the adjoint model. The variational estimation method is scalable, fast converging, and offers a convenient framework for introducing additional constraints relevant to hydrology. It can be used both for calibrating the parameters and estimating the initial state of the hydrological system for short range forecasting (in a manner used in weather forecasting). The study area is the Gardon d’Anduze watershed where four gauging stations are available. In numerical experiments, the benefits of using the distributed against the uniform calibration are analysed in terms of the model predictive performance. Distributed calibration shows encouraging results with better model prediction at gauged and ungauged locations.

Geoarchaeological and Paleohydrological Evidence for a Clovis-Age Drought in North America and Its Bearing on Extinction

1991 ◽  
Vol 35 (3-Part1) ◽  
pp. 438-450 ◽  
Author(s):  
C. Vance Haynes
Keyword(s):  
North America ◽  
Great Basin ◽  
Water Table ◽  
Marked Decrease ◽  
Northern Europe ◽  
Dry Period ◽  
Human Predation ◽  
Water Table Rise ◽  
Algal Mat ◽  
Game Animals

AbstractAt the Murray Springs Clovis site in southeastern Arizona, stratigraphic and geomorphic evidence indicates that an abnormally low water table 10,900 yr B.P. was followed soon thereafter by a water-table rise accompanied by the deposition of an algal mat (the “black mat”) that buried mammoth tracks, Clovis artifacts, and a well. This water-table fluctuation correlates with pluvial lake fluctuations in the Great Basin during and immediately following Clovis occupation of that region. Many elements of Pleistocene megafauna in North America became extinct during the dry period. Oxygen isotope records show a marked decrease in δ18O correlated with the Younger Dryas cold-dry event of northern Europe which ended 10,750 yr B.P., essentially the same time as the water table began to rise in southeastern Arizona. Clovis hunters may have found large game animals easier prey when concentrated at water holes and under stress. If so, both climate and human predation contributed to Pleistocene extinction in America.

scholarly journals Spontaneous revegetation of a peatland in Manitoba after peat extraction: diversity of plant assemblages and restoration perspectives

Botany ◽  
2018 ◽  
Vol 96 (11) ◽  
pp. 779-791 ◽  
Author(s):  
Félix Gagnon ◽  
Line Rochefort ◽  
Claude Lavoie
Keyword(s):  
Water Table ◽  
Plant Cover ◽  
High Water ◽  
Point Of View ◽  
Water Table Level ◽  
Peat Extraction ◽  
Peatland Restoration ◽  
Water Ph ◽  
Plant Assemblages ◽  
A Site

There are very few studies on the spontaneous revegetation of cutover fens or bogs from which peat has been extracted to the minerotrophic layers. Most peatlands with fen-type residual peat have problems regenerating a plant cover satisfactorily from a restoration point of view. We nevertheless found a site (Moss Spur, Manitoba, Canada) presenting a substantial and diversified spontaneous plant cover. We estimated that the site would provide insights about natural revegetation processes operating in peatlands. Vegetation assemblages and environmental conditions were surveyed 19 years after extraction activities ceased. Moss Spur has densely revegetated (163 plant species, vegetation cover of 94%) with minimal human assistance. However, the composition of plant assemblages varies considerably across the site, depending on certain abiotic variables, particularly water pH, water table level, and the thickness of the residual peat layer. Moss Spur was remarkably wet considering the past peat extraction activities and the absence of active rewetting procedures. The high water table level may in part explain the successful revegetation. However, plant assemblages were not of equal quality from a restoration perspective. Some assemblages were highly diversified, and especially those dominated by Scirpus cyperinus, a species that should be further considered in peatland restoration projects to direct the recovery of the peatland towards a natural fen species composition.

scholarly journals Predicting sedimentary bedrock subsurface weathering fronts and weathering rates

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jiamin Wan ◽  
Tetsu K. Tokunaga ◽  
Kenneth H. Williams ◽  
Wenming Dong ◽  
Wendy Brown ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Table ◽  
Pyrite Oxidation ◽  
Base Cation ◽  
Subsurface Water ◽  
Nitrogen Budgets ◽  
Weathering Rates ◽  
Marine Shale ◽  
Bedrock Weathering ◽  
Water Saturated

AbstractAlthough bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha−1 y−1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.

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